Michael Thielscher

Professor
School of Computer Science and Engineering
UNSW Australia



Associate Director
iCinema Research Centre
UNSW Australia



Adjunct Professor
School of Computing and Mathematics
Western Sydney University

Michael Thielscher
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  Avaliable Tutorial Slides

  • IJCAI-09 Tutorial "New Trends in General Game Playing"

    General Game Playing (GGP) is concerned with the development of systems that can play well an arbitrary game solely by being given the rules of the game. GGP has recently been proposed as one of the grand contemporary AI challenges, which encompasses a variety of research areas including

    • Knowledge Representation and Reasoning
    • Heuristic Search and Planning
    • Computational Game Theory
    • Learning


    GGP has a number of immediate potential applications, including universal game computers, autonomous trading agents, and advice takers for economic decision problems. This tutorial gives an introduction to the foundations of GGP systems and provides an in-depth insight into recent results, state-of-the-art techniques, and current and future research trends and developments.
    This tutorial is directed at every AI researcher who wants to gain an insight into General Game Playing as a new, grand AI challenge, and who wants to learn about the key techniques, latest results, and current research trends in the design of GGP systems. The only required background is some basic knowledge of standard first-order logic.

  • KR-08 Tutorial "KR Techniques for General Game Playing"

    A General Game Player is a program that accepts formal descriptions of arbitrary games and plays these games without human intervention. One of the grand challenges for Artificial Intelligence, General Game Playing requires to combine techniques from a wide range of areas including knowledge representation, automated reasoning, heuristic search, planning, and learning. This tutorial will focus on the challenges for Knowledge Representation and Reasoning raised by General Game Playing:

    • Formalizing game rules
    • Mapping game descriptions to efficient representations
    • Extracting knowledge from game descritions
    • Proving properties of games


  • AAAI-08 Tutorial "General Game Playing"

    General Game Playing is concerned with the development of systems that can play well arbitrary games solely by being given the rules of a game. This raises a number of issues different from traditional research in game playing, where it is assumed that the rules of a game are known to the programmer. Systems able to play hitherto unknown games cannot be given game-specific knowledge. They rather need to be endowed with high-level cognitive abilities such as general strategic thinking, abstract reasoning, and learning. General Game Playing has recently been proposed as one of the grand contemporary AI challenges, encompassing a variety of research areas such as knowledge representation and reasoning, heuristic search and planning, game playing, and learning. General Game Playing has a number of immediate potential applications, including game playing programs that can be adapted by their users and advice giving systems for negotiations, marketing strategies, pricing etc.

    This tutorial is directed at every AI researcher who wants to gain an insight into General Game Playing as a method to formalize and solve general decision-making problems in competitive environments. The only required background is some basic knowledge of standard first-order logic.

  • IJCAI-07 Tutorial "The Art and Science of Action Programming Languages"

    Intelligent software agents, general game players, and high-level controlers for autonomous robots are three examples of systems for which the ability to reason about their actions and their effeects play a key role. For this purpose, action programming languages have recently been developed on the basis of 40 years of research in knowledge representation. An action programming language provides a complementary supplement to subsymbolic methods for the reactive control systems: thanks to a high level of abstraction, symbolic reasoning allows to solve complex tasks with huge state spaces by high-level programs which are easy to write, understand, and maintain and which allow one to implement flexible planning and acting strategies. Highly optimized implementations have recently been developed for various action programming languages.

    This tutorial gives an introduction to selected languages and systems. The tutorial provides an insight into the underlying mathematics and into the advantages and disadvantages of these languages in comparison. A variety of successful applications of action programming languages are discussed with a focus on general game playing on the one hand, and the combination with low-level control of autonomous robots on the other hand.
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